Processing ARSF remote sensing data with open source GIS tools

The UK National Environment Research Council’s Airborne Research and Survey Facility (NERC ARSF) is an aircraft used for scientific research. The on-board instruments include LiDAR, high resolution camera, and multispectral and hyperspectral infrared scanners. The aim of this post is to share an article and slides from a talk that I gave in 2009 that demonstrate how these data can be processed with free and open source tools.

The slides and articles also illustrate some of the ways that GRASS GIS can be used to process remote sensing data in general.

Getting started with GRASS GIS

Multispectral infrared data channels combined in GRASS to highlight different landscape/vegetation features. If you have visited Iceland, you may recognise the Nesjavellir geothermal plant, with its steam and warm river. Click the image to enlarge.

GRASS GIS is a fully-featured open source GIS package. In talk and article I describe using it to process LiDAR point clouds, orthorectify aerial photos, calculate slope/aspect maps, digitise geological information, import field data and to visualise and export data in a variety of formats. From a remote-sensing perspective, the Image Processing features include things like image classification and fusion.

Early versions of GRASS were mainly command-line based, so the learning curve can be a bit steep, but the GUI has improved significantly (especially from 6.4.2 onwards). The command line has the advantage of easy scripting, and the latest versions are moving to Python which will make it simple to include GIS processing in other workflows.

The following tips will help you get started with GRASS:

Install GRASS from the website. As it was initially developed on the UNIX operating system, the Linux and Mac versions are better. Windows users should install the OSGeo4W package, which also includes a number of other useful programs e.g. QGIS.

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Yes, all NERC ARSF data has to be posted to a repository within two years after the project. If you register with an account, you can download my data (Flight: IPY07-02) or any others. The catalogue is here: